Recursive least-squares-based subspace tracking
Bin Yang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
In this paper, we introduce a new interpretation of the signal subspace as the solution of an unconstrained minimization problem. We show that recursive least squares techniques can be applied to track the signal subspace recursively by making an appropriate projection approximation of the cost function. The resulting algorithms have a computational complexity of O(nr) where n is the input vector dimension and r(r